Within the field of language translation, many techniques may be utilized to identify, normalize, and/or translate temporal elements of an expression that are associated with a date, such as a calendar date, a weekday, a time of day, or a duration. These techniques often involve the configuration of a device to apply a translation logic to the expression, such as a rule set comprising a set of manually developed rules that respectively specify the translation of a temporal element of an expression into a translated expression, or a machine learning recognizer that has been trained using a training data set to facilitate the translation of temporal elements into translated expressions. Many such techniques may be devised and implemented for a variety of contexts; e.g., a first implementation may comprise a comparatively simple rule set that provides basic date translation for use on a mobile device having comparatively limited computational resources, and a second implementation may comprise a robust machine-learning recognizer and a sophisticated logic that together provide sophisticated, highly accurate date translation for use on computationally plentiful servers.